Enterprise AI security is an architectural discipline, not a compliance checklist. This article frames the real threat landscape, from prompt injection and model poisoning to sensitive data leakage and over-permissive access, and describes the production architecture patterns that address these risks at scale. Written for CEOs, CTOs, and board-level leaders, it covers secure RAG design, data isolation, policy-driven access control, human oversight frameworks, and the governance structures that make AI deployments trustworthy, auditable, and regulatorily defensible. The conclusion is direct: organizations that embed security into AI architecture from the beginning will scale further, access higher-value markets, and carry lower long-term risk than those who treat security as an afterthought.